How Interpersonal Distance Between Avatar and Human Influences Facial Affect Recognition in Immersive Virtual Reality.

Juan Del Aguila,Luz M González-Gualda,Antonio Fernández-Caballero,Arturo S García,Patricia Fernández-Sotos,María Angeles Játiva

doi:10.3389/fpsyg.2021.675515

Abstract

Purpose: The purpose of this study was to determine the optimal interpersonal distance (IPD) between humans and affective avatars in facial affect recognition in immersive virtual reality (IVR). The ideal IPD is the one in which the humans show the highest number of hits and the shortest reaction times in recognizing the emotions displayed by avatars. The results should help design future therapies to remedy facial affect recognition deficits.Methods: A group of 39 healthy volunteers participated in an experiment in which participants were shown 65 dynamic faces in IVR and had to identify six basic emotions plus neutral expression presented by the avatars. We decided to limit the experiment to five different distances: D1 (35 cm), D2 (55 cm), D3 (75 cm), D4 (95 cm), and D5 (115 cm), all belonging to the intimate and personal interpersonal spaces. Of the total of 65 faces, 13 faces were presented for each of the included distances. The views were shown at different angles: 50% in frontal view, 25% from the right profile, and 25% from the left profile. The order of appearance of the faces presented to each participant was randomized.Results: The overall success rate in facial emotion identification was 90.33%, being D3 the IPD with the best overall emotional recognition hits, although statistically significant differences could not be found between the IPDs. Consistent with results obtained in previous studies, identification rates for negative emotions were higher with increasing IPD, whereas the recognition task improved for positive emotions when IPD was closer. In addition, the study revealed irregular behavior in the facial detection of the emotion surprise.Conclusions: IVR allows us to reliably assess facial emotion recognition using dynamic avatars as all the IPDs tested showed to be effective. However, no statistically significant differences in facial emotion recognition were found among the different IPDs.

Highlights

Virtual reality (VR) is a powerful tool that allows the creation of lifelike environments and situations by imitating the physical world digitally
The overall success rate in facial emotion identification was 90.33%, being D3 the interpersonal distance (IPD) with the best overall emotional recognition hits, statistically significant differences could not be found between the IPDs
No statistically significant differences in facial emotion recognition were found among the different IPDs

Summary

Introduction

Virtual reality (VR) is a powerful tool that allows the creation of lifelike environments and situations by imitating the physical world digitally. Most of the research focused on the processes underlying anxiety disorders and their treatment. Research has been extended to other mental disorders such as major depressive disorder, bipolar disorder, and schizophrenia (Chen et al, 2021; Vass et al, 2021). This body of research has concluded that VR is a valuable tool for assessing the presence of symptoms in valid and controlled settings (Rus-Calafell et al, 2018; Browning et al, 2020; Fernández-Sotos et al, 2020; Hørlyck et al, 2021). It has the potential to facilitate the learning of new emotional and behavioral responses and can be applied to cognitive rehabilitation (Burin et al, 2020) and social cognition training interventions (Rus-Calafell et al, 2018)

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